Chair of Digital Health

Imagine personalised health assistance that is omnipresent and continuously available to everyone while being intelligible – we are working to realise this vision.

Research Areas

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Background It is considered impossible to know the maximum possible learning performance of a machine learning (ML) algorithm on a given dataset before running the algorithm. The performance of an ML algorithm depends on many factors, such as the quality and size of the data, the complexity of t...

Dr. Andreas Rowald gave a talk at the ZiMT Journal Club on May 24, 2022. Title: Digital twins can steer neurostimulation towards precision medicine Abstract: Neurostimulation strategies are potentially effective and risk-, time- and cost-limited treatments for the approximately 22% of Europea...

The Chair of Digital Health develops AI-based methods for the analysis of healthy behavior, increasing health literacy, as well as for medical decision support for the personalized early detection of diseases, diagnosis, therapy and prevention. The exhibitions and demonstrations show project exampl...

Friedrich-Alexander-Universität Erlangen-Nürnberg